Free-Gate: Planning, Control And Policy Composition via Free Energy Gating
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arXiv
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| Format: | Preprint |
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2024
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| _version_ | 1866912509885153280 |
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| author | Rossi, Francesca Garrabé, Émiland Russo, Giovanni |
| author_facet | Rossi, Francesca Garrabé, Émiland Russo, Giovanni |
| contents | We consider the problem of optimally composing a set of primitives to tackle planning and control tasks. To address this problem, we introduce a free energy computational model for planning and control via policy composition: Free-Gate. Within Free-Gate, control primitives are combined via a gating mechanism that minimizes variational free energy. This composition problem is formulated as a finite-horizon optimal control problem, which we prove remains convex even when the cost is not convex in states/actions and the environment is nonlinear, stochastic and non-stationary. We develop an algorithm that computes the optimal primitives composition and demonstrate its effectiveness via in-silico and hardware experiments on an application involving robot navigation in an environment with obstacles. The experiments highlight that Free-Gate enables the robot to navigate to the destination despite only having available simple motor primitives that, individually, could not fulfill the task. |
| format | Preprint |
| id |
arxiv_https___arxiv_org_abs_2412_06636 |
| institution | arXiv |
| publishDate | 2024 |
| record_format | arxiv |
| spellingShingle | Free-Gate: Planning, Control And Policy Composition via Free Energy Gating Rossi, Francesca Garrabé, Émiland Russo, Giovanni Optimization and Control Robotics Systems and Control We consider the problem of optimally composing a set of primitives to tackle planning and control tasks. To address this problem, we introduce a free energy computational model for planning and control via policy composition: Free-Gate. Within Free-Gate, control primitives are combined via a gating mechanism that minimizes variational free energy. This composition problem is formulated as a finite-horizon optimal control problem, which we prove remains convex even when the cost is not convex in states/actions and the environment is nonlinear, stochastic and non-stationary. We develop an algorithm that computes the optimal primitives composition and demonstrate its effectiveness via in-silico and hardware experiments on an application involving robot navigation in an environment with obstacles. The experiments highlight that Free-Gate enables the robot to navigate to the destination despite only having available simple motor primitives that, individually, could not fulfill the task. |
| title | Free-Gate: Planning, Control And Policy Composition via Free Energy Gating |
| topic | Optimization and Control Robotics Systems and Control |
| url | https://arxiv.org/abs/2412.06636 |